TOTES Model

Online advertising is different from traditional advertising in several important ways, the most important of which relates with user data. On one hand it involves the collection of user data, and on the other the exploitation of the collected data. The second important difference is how online advertising places messages in context that blur the lines of what is advertising and what is not. Examples of this include native advertising, advergames, and social influence campaigns. The third aspect has to do with how messages can be specificly tailored to maximize deceptiveness, even at a level of a single individual. Examples of techniques include micro-targeting, dynamic creatives and AI generated copy. These three aspects – data, messaging, and context – make up the three vectors on which offensive techniques can be excecuted by advertisers and their partners.

Online advertising marks an important point in the history of advertising; there is a notable shift in the society from accept-and-avoid strategies, to reject-and-prevent strategies. Most notable development highlighting this shift is ad blocking, and how more than 20% of internet users already use an ad blocker. Well implemented ad blocking effectively mitigates all threats on the data vector, and many threats on the messaging vector, but does not provide sufficient protection against offensive tactics that leverage the context vector. For example, an ad blocker would not recognize a social influence campaign, or advergame, and therefore would not be able to protect the user from those threaths. This reveals an important shortcoming in the online advertising threat landscape; advertisers and their partners have an upper hand over the internet users. If internet users, or segments of users such as children, increase defensivess on one vector, advertisers and their partners can simply invest more on the two others.

TOTES Model addresses the gaps in invidual tactics such as ad blocking, by providing a comprehensive guideline for embracing reject-and-prevent strategies for the protection of children. When implemented correctly, the suggested behavior changes lead to a safer, more meaningful online experience for children. The guidance includes a comprehensive review of defensive technologies, and relevant literature, while providing evidence and reasoning for overcoming common arguments against adopting such strategies.